Evidence map›Paper›PMID 26888852›Full record

Observational studyRheumatology (Oxford, England)2016

Performance of Gout Impact Scale in a longitudinal observational study of patients with gout.

Beth Wallace, Dinesh Khanna, Cleopatra Aquino-Beaton, Jasvinder A Singh, Erin Duffy, David Elashoff, Puja P Khanna

Open access · bronzeAbstract readMulticenter StudyObservational StudyValidation Study
In one paragraph

Observational study in Rheumatology (Oxford, England), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
1.4field-weighted citation impact, top 20% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 20 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Trial
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Use of the Gout Impact Scale to Evaluate Quality of Life in Chinese Subjects with Gout: A Cross-Sectional Study.Medical science monitor : international medical journal of experimental and clinical research · 2020
    Observational
  11. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 4 institutions in 1 country.

Beth WallaceDivision of Rheumatology, University of Michigan, Ann Arbor, MI.
Dinesh KhannaDivision of Rheumatology, University of Michigan, Ann Arbor, MI.
Cleopatra Aquino-BeatonDepartment of Medicine/Division of Rheumatology, VA Greater Los Angeles Healthcare System, Los Angeles, CA.
Jasvinder A SinghDepartment of Medicine/Division of Rheumatology, University of Alabama and Birmingham VA, Birmingham, AL.
Erin DuffyUniversity of California Los Angeles Department of Medicine Statistics Core, Los Angeles, CA and.
David ElashoffUniversity of California Los Angeles Department of Medicine Statistics Core, Los Angeles, CA and.
Puja P KhannaDivision of Rheumatology, University of Michigan, Ann Arbor, MI, Department of Medicine/Division of Rheumatology, Ann Arbor VA Medical Center, Ann Arbor, MI, USA pkhanna@med.umich.edu.
University of Michigan–Ann Arbor · USUniversity of California, Los Angeles · USUniversity of Alabama · USVA Greater Los Angeles Healthcare System · US

Funding

Outcomes Research in Rheumatic DiseasesK24AR063120 · NIAMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI KHANNA, DINESH · 2012 to 2022
$1.6M
NIAMS NIH HHS K24 AR063120
6 · The paper itself

Abstract

objectiveThe aim was to evaluate the reliability, validity and responsiveness to change of the Gout Impact Scale (GIS), a disease-specific measure of patient-reported outcomes, in a multicentre longitudinal prospective cohort of gout patients.

methodsSubjects completed the GIS, a 24-item instrument with five scales: Concern Overall, Medication Side Effects, Unmet Treatment Need, Well-Being during Attack, and Concern Over Attack. The total GIS score was calculated by averaging the GIS scale scores. HAQ-Disability Index (HAQ-DI), Short Form (SF)-36 physical and mental component summaries (PCS and MCS) and physician and patient gout severity assessments were also completed. Reliability was assessed with Cronbach's α. Baseline GIS scores were compared in subjects with and without gout attacks in the past 3 months using Wilcoxon rank sum tests. Multivariate linear regression was used to evaluate predictors of total GIS. Pearson's correlation coefficients 0.24-0.36 were considered moderate and >0.37 considered large. The effect size for responsiveness to change was interpreted as follows: 0.20-0.49 small, 0.50-0.79 medium and >0.79 large.

resultsIn 147 subjects, reliability was acceptable for total GIS (0.93) and all GIS scales (0.82-0.94) except Medication Side Effects and Unmet Treatment Need. Total GIS and all scales except Medication Side Effects discriminated between subjects with and without recent gout attacks (P < 0.05). Total GIS showed moderate-to-large correlations with HAQ-DI, SF-36 PCS and MCS (0.33-0.46). Improvement in total GIS tracked with improved physician and patient severity scores. Worsening physician severity score and recent gout attack predicted worsening total GIS.

conclusionTotal GIS score is reliable, valid and responsive to change in patients with gout, and differentiates between subjects with and without recent gout attacks.

Indexed as

Patient Reported Outcome MeasuresSeverity of Illness IndexAgedDisability EvaluationFemaleGoutHumansLinear ModelsLongitudinal StudiesMaleMiddle AgedProspective StudiesReproducibility of ResultsSurveys and QuestionnairesUnited StatesUnited States Department of Veterans Affairsgoutoutcomesvalidated measure

Identifiers

PMID26888852
PMCPMC5854089
OpenAlexW2375209674

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.